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README.md

@@ -138,6 +138,10 @@ Cycle 3: train (batch=3, 22B, 14.5GB)  -> prune -> defrag                  (2.8x
 
 40% faster total training and a 33% smaller final model.
 
+### Head Mitosis
+
+Pruning frees slots. Mitosis fills them. When a head is overutilized, it gets cloned into a pruned slot — each copy at 50% gate value to maintain output continuity. After continued training, the clones **diverge and specialize**, like cell differentiation after biological mitosis. The model grows new specialized capacity exactly where it's needed.
+
 **Read the full paper**: [Experiential Plasticity: Transformers That Grow Their Own Architecture From Experience](https://github.com/CambrianTech/continuum/blob/main/docs/papers/EXPERIENTIAL-PLASTICITY.md)
 
 ## Output Samples